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The science of quantifying the human perception of color, or “colorimetry,” defines colors as vectors in a color space or color model. The conversion of vectors from one color space to another color space using a mapping function is commonly used in image processing for printing or displaying images. For example, when an image input device, such as a scanner, a digital camera, or a computer, uses a different color space than that of an image output device, such as a printer or a display, color space conversion is typically performed to maintain the color integrity of an image.
Color space conversion is generally a challenging process because the mapping function from one color space to another color space is rarely linear. That is, the conversion algorithm necessary for one area in the color space is not effective in a second area in the color space. Rather than mathematically performing the color space conversion, a look up table may be used to perform cost effective color space conversion.
A typical example of a color space includes three color components, with each color component represented by eight bits, or 24 bits total for all of the color components of any given color in the color space. Using this example, there are (28)3 possible colors, requiring a lookup table large enough to store 224 values for both the input and output color spaces.